Image data processing is used to inspect items during and after the manufacturing process. Such image data is typically gathered using a digital camera or other device that digitizes image data within the focal field of the device. The digitized image data is then analyzed, either manually or by software systems or other digital systems.
In cases where the image data is more complex, it is often necessary to manually review the image data before software systems can be used. For example, image data of dies that have been formed on a silicon wafer may be inspected by software systems. Nevertheless, areas of the die may have to be manually selected that cannot be analyzed by the software systems, such as areas that contain image data that will cause the software systems to register a false indication of a problem. In other circumstances, it is easier to select areas that are to be inspected, rather than areas that are to be excluded from inspection.
Therefore, although analysis of image data by software systems is useful, manual selection of image data may still be required. One area in which such manual selection is required is the selection of certain repetitive features, such as bond pads of a silicon wafer die. Because the image data of border areas surrounding bond pads can vary significantly, analysis of the image data by a software system to locate bond pads can result in an unacceptable number of false positives. As a result, it is necessary to manually identify each bond pad on a reference die before a software system can be used to analyze the bond pad image data to determine whether damage or other unacceptable conditions exist.
In accordance with the present invention, a system and method for locating features in image data are provided that overcome known problems with locating features.
In particular, a system and method for a locating features in image data are provided that allow discrete portions of image data to be used to search for the features such that the number of instances in which a feature is improperly identified is minimized.
In accordance with an exemplary embodiment of the present invention, a system for analyzing image data is presented. The system includes a first component system. The first component system compares first component data, which can be pixel data of a first user-selected component of the feature, to first test image data, which can be selected by scanning image data of a device, such as a die cut from a silicon wafer. The system also includes second component system that is connected to the first component system, such as through data memory locations of a processor. The second component system compares second component data to second test image data if the first component system finds a match between the first component data and the first test image data. The second test image data is selected based upon the first test image data, such as by using a known coordinate relationship between pixels of the first component data and the second component data.
The present invention provides many important technical advantages. One important technical advantage of the present invention is a feature location system and method that do not generate incorrect results because of non-uniform image data that may lie in the border of the feature. Such non-uniform image data may be included in a test image that is used to identify the feature, and can result in incorrect results. The present invention allows components of features to be selected from areas that have minimal non-uniform image data, thus minimizing the number of incorrect results.